a signal use resnet denoise in matlab

To use ResNet for denoising in MATLAB, you can follow these steps:

  1. Load the noisy image and convert it to grayscale (if needed).
main.m
noisyImg = imread('noisy_image.png');
grayImg = rgb2gray(noisyImg);
68 chars
3 lines
  1. Create the ResNet denoising network using denoisingResNet function.
main.m
%Create a denoising network with default settings
resnetDenoise = denoisingResnet;
83 chars
3 lines
  1. Set the options for the denoising algorithm.
main.m
options = trainingOptions('adam', ... %Optimizer
    'Epochs', 20, ... %Number of training epochs
    'MiniBatchSize', 128, ... %Mini-batch size
    'CheckpointPath', 'path/to/checkpoints', ... %Checkpoint directory
    'Plots', 'training-progress'); %Display training progress
278 chars
6 lines
  1. Train the network with noisy and clean image pairs.
main.m
denoisedImg = denoiseImage(noisyImg, resnetDenoise, 'ExecutionEnvironment', 'cpu', 'Verbose', true);
101 chars
2 lines
  1. Save the denoised image.
main.m
imwrite(denoisedImg, 'denoised_image.png');
44 chars
2 lines

gistlibby LogSnag